Federated target trial emulation using distributed observational data for treatment effect estimation

Federated target trial emulation using distributed observational data for treatment effect estimation

Target trial emulation (TTE) aims to estimate treatment effects by simulating randomized controlled trials using real-world observational data. Applying TTE across distributed datasets shows great promise in improving generalizability and power but is always infeasible due to privacy and data-sharing constraints. Here we propose a Federated Learning-based TTE framework, FL-TTE, that enables TTE across multiple sites without sharing patient-level…

A Deep Dive into federated information governance with Objective

With data sprawl and data silos an exponentially growing issue for the public sector, federated information management helps organisations remain compliant with governance regulations and maintain high levels of security ...

Using Real-World Data To Bridge The Clinical Trial Divide - Data Intelligence

Image Credit: © photon_photo – stock.adobe.com Key takeaways Clinical trial populations often don’t reflect the diversity or complexity of real-world patients, particularly in community care settings. Real-world evidence (RWE) studies are essential for building physician confidence and expanding adoption post-approval, especially in underrepresented populations. Access to representative datasets—beyond academic centers—is critical, and emerging…